Abstract
Purpose The purpose of this paper is to maximize the total demand covered by the established additive manufacturing and distribution centers and maximize the total literal weight assigned to the drones. Design/methodology/approach Disaster management or humanitarian supply chains (HSCs) differ from commercial supply chains in the fact that the aim of HSCs is to minimize the response time to a disaster as compared to the profit maximization goal of commercial supply chains. In this paper, the authors develop a relief chain structure that accommodates emerging technologies in humanitarian logistics into the two phases of disaster management – the preparedness stage and the response stage. Findings Solving the model by the genetic and the cuckoo optimization algorithm (COA) and comparing the results with the ones obtained by The General Algebraic Modeling System (GAMS) clear that genetic algorithm overcomes other options as it has led to objective functions that are 1.6% and 24.1% better comparing to GAMS and COA, respectively. Originality/value Finally, the presented model has been solved with three methods including one exact method and two metaheuristic methods. Results of implementation show that Non-dominated sorting genetic algorithm II (NSGA-II) has better performance in finding the optimal solutions.
Highlights
Any occurrence that causes damage, destruction, ecological disruption, loss of human life, human suffering or the deterioration of health and health services on a scale sufficient to warrant an extraordinary response from outside the affected community or area is called disaster
We were able to successfully prove that this can be applied to the preparedness stage, the mitigation stage and the response stage of the disaster relief chain
This paper proves how emerging technologies like additive manufacturing (AM) or 3 D printing and drones can be accommodated into existing models and their potential to reduce delivery time and optimize financial resources
Summary
Any occurrence that causes damage, destruction, ecological disruption, loss of human life, human suffering or the deterioration of health and health services on a scale sufficient to warrant an extraordinary response from outside the affected community or area is called disaster. What can contribute greatly to these goals are new technologies if they are extensively introduced and applied in the field of crisis management, for example, unmanned aerial vehicles (UAV), robots, additive manufacturing (AM), software and satellites It can be seen this process is highly important, in the high amount of investment realized by individual nations and international firms. To guarantee that the managers are supported adequately by novel technologies for making their vital decisions, it is necessary to research and test the solutions, ideally under authentic conditions, before applying them in disaster response (Zwęglinski, 2020). This is especially important for health-care services. It is rare for both issues to be considered simultaneously in an HSC, in most cases being used alone or focusing on the diverse goals of locating models
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